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What are the advantages and disadvantages of using a neural network for classification tasks?

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Advantages of using a neural network for classification tasks include its ability to represent complex decision boundaries, its capacity to learn interaction between features, and its increased flexibility in recognizing patterns within data. Neural networks also have a very low bias and are able to generalize patterns from data more efficiently than other classification techniques like decision trees. However, the biggest disadvantage of neural networks is the difficulty in interpreting its output and its reliance on huge amounts of data. Additionally, the results of a neural network cannot be easily examined and validated, which is necessary to ensure that no erroneous decisions are taken.